Chaotic Analysis of the GDP Time Series

Abstract

The goal of this paper is to analyze the Czech Gross domestic product (GDP) and to find chaos in the Czech GDP. At first we will estimate the time delay and the embedding dimension, which is needed for the Lyapunov exponent estimation and for the phase space reconstruction. Subsequently we will compute the largest Lyapunov exponent, which is one of the important indicators of chaos. Then we will calculate the 0-1 test for chaos. Finally we will compute the Hurst exponent by Rescaled Range analysis and by dispersional analysis. The Hurst exponent is a numerical estimate of the predictability of a time series. In the end we will display a phase portrait of detrended GDP time series. The results indicated that chaotic behaviors obviously exist in GDP. © Springer International Publishing Switzerland 2013.